Predictive analytics involves a wide range of statistical tools and methods that allow an analyst to build a powerful predictive model. Explore the importance of statistics and probability theory in predictive analytics.
Learning Objectives
Importance of Statistics in Analytics
- start the course
- recognize the role of statistics in predictive analytics
- recognize attributes of qualitative, quantitative, discrete, and continuous data
- recognize features of data measurement scales
- recognize features of descriptive and inferential statistics
Overview of Probability Theory
- recognize basic features of probability and the types of probabilistic events
- apply addition and multiplication rules for a probabilistic event
- apply Bayes theorem in a given situation
- distinguish between permutations and combinations
Using Statistics in Predictive Analytics
- recognize how to reduce the margin of error
- recognize how confidence intervals (CI) are used for hypothesis testing
- recognize key features of testing for differences in mean and testing for differences in proportion
- determine if a data sample is representative of the data population